Progressive Probabilistic Hough Transform

In the paper we present the Progressive Probabilistic Hough Transform (PPHT). Unlike the Probabilistic Hough Transform 4] where Standard Hough Transform is performed on a pre-selected fraction of input points, PPHT minimises the amount of computation needed to detect lines by exploiting the di erence in the fraction of votes needed to reliably detect lines with di erent numbers of supporting points. The fraction of points used for voting need not be speci ed ad hoc or using a priori knowledge, as in the Probabilistic Hough Transform; it is a function of the inherent complexity of data. The algorithm is ideally suited for real-time applications with a xed amount of available processing time, since voting and line detection is interleaved. The most salient features are likely to be detected rst. Experiments show PPHT has, in many circumstances, advantages over the Standard Hough Transform.

• Type: Conference
• Year: 1998
• Where: BMVC
• Authors: Jiri Matas, Charles Galambos, Josef Kittler
• Keywords: BMVC 1998, Computer Vision, Hough Transform, Probabilistic Hough Transform, Standard Hough Transform